tbuckley/cabot-search huggingface dataset:
Validation of a novel and rapid reagent free assay to predict outcomes for adjuvant therapy decision making in hormone receptor-positive breast cancer.
Authors: Charles Coombes, Hemmel Amrania, Christina Angelou, Zamzam Al-Khalili, Ian O. Ellis, Darius Francescatti, Chris Phillips, Andrew R. Green, Nicholas Wright, Emad A. Rakha, Carlo Palmieri
Journal: Journal of Clinical Oncology (2023)

545 Background: Digistain is a mid-infrared imaging technology that assesses aneuploidy by measuring the nuclear-to-cytoplasmic chemical ratio in the cellular content of tissues to generate the Digistain Index (DI). DI correlates with tumor grade and shows promise for risk stratification. Here we investigated whether DI could predict clinical outcomes in patients with early breast cancer to guide decision making regarding subsequent adjuvant chemotherapy. Methods: Infrared spectrometry was performed on existing tissue microarrays to determine the DI of 801 patients with hormone receptor-positive, HER 2-negative primary breast cancer with ≤3 positive lymph nodes who had received systemic endocrine therapy only. Multivariate logistic modelling incorporated the DI with pathological features to generate the Digistain Prognostic Score (DPS). Receiver operator characteristics curves were used to assess the ability of DPS to predict 5- and 10-year progression-free survival (PFS), recurrence and overall survival (OS). Results: In a Cox-regression analysis, the hazard ratio (HR) of DI to predict OS was 4.49 (95% CI 1.08–18.67; P=0.039) compared with HRs in the range of 1.04–1.81 (all P &lt; 0.001) for age, tumor grade, tumor size and lymph node stage. In multivariate modelling analysis, DPS was consistently highly accurate and had negative predictive values for PFS, recurrence, and OS at 5 and 10 years that were similar, if not superior, to existing genomic-based tests. Using the DPS, the HRs for Kaplan-Meier curves for low- vs. high-risk classification were statistically significant (P&lt;0.001) for PFS, recurrence and OS (1.80, 1.83 and 2.49, respectively). Conclusions: In patients with early breast cancer, DPS showed high accuracy and predictive performance, and was able to stratify patients into low or high risk. Considering its low cost and ability to provide almost immediate prognostic information, DPS has the potential to offer clinical utility to reduce the use of unnecessary chemotherapy.
Explainable AI and machine learning algorithms to predict treatment failures for patients with cancer.
Authors: Muddassar Farooq, Muhammad Usamah Shahid
Journal: Journal of Clinical Oncology (2023)

e13577 Background: Cancer patients may undergo lengthy and painful chemotherapy treatments, comprising several successive regimens or plans. Treatment inefficacy and other adverse events can lead to discontinuation (or failure) of these plans, or prematurely changing them, which results in a significant amount of physical, financial, and emotional toxicity to the patients and their families. In this research work, we build AI driven treatment failure models that utilize the real-world evidence gathered from patients’ profiles available in an oncology EMR/EHR system, with a goal of predicting the likelihood of a plan being discontinued at the time of its prescription. The selected AI models achieve a prediction accuracy of more than 80% and also provide reasons for their inference. Methods: Inclusion and Exclusion Criteria: Deidentified and anonymized electronic health records of patients, with their prescribed chemotherapies, for five different primary cancer diagnoses - ICD10 codes C18, C34, C50, C61 and C90 - that have the highest plan discontinuation rates between the years 2015 and 2022 are analyzed. All patients of other cancer types are excluded. AI Models: Unique features, that influence the treatment failure, for each cancer type are engineered by using therapeutic classification of drugs, diagnoses codes, comorbidity scores, tumor and biomarker information that is extracted from the notes and lab tests. We only use features that are available at the time of selecting a treatment plan. Several machine learning classifiers are investigated, and three tree ensembles - random forests, Xgboost and boosted forests - are further evaluated on the validation set to fine tune learning parameters with an objective to reduce the complexity of decision trees for providing better interpretability without significantly compromising the accuracy. Results: Our pilot studies reveal that boosted forests comprising of 5 random forests, each with 5 trees of depth 10 offer the best compromise between performance and interpretability. The models once trained are evaluated on unseen datasets and four performance measures of AI models are reported. On average, 15 rules are autonomously generated for a treatment failure inference for each cancer type and generally 6 of them have a significant support of 30 samples or greater. Conclusions: Machine learning algorithms for predicting treatment efficacy of chemotherapy regimens by deriving inference from the patients’ EMR/EHR data is an emerging yet challenging research domain. Our studies demonstrate that AI models like boosted forests provide the optimal models for treatment failure use case. In future, we want to validate the system in controlled clinical trials with the help of oncologists. [Table: see text]
Impact of breast density on classification of infrared spectroscopy for breath-based breast cancer screening.
Authors: Farah Naz, Amy Grace Groom, MD Mohiuddin, Arpita Sengupta, Margot J. Burnell, Trisha Daigle-Maloney, James Charles Roger Michael, Stephen Graham, Gisia Beydaghyan, Christian Bailey Morrell, Robyn Larracy, Erik Scheme
Journal: Journal of Clinical Oncology (2023)

e13558 Background: While mammography is currently the standard of care for breast cancer screening, dense breast tissue can significantly degrade results. Alternatively, infrared spectroscopy analysis of breath offers a highly sensitive method for identifying exhaled volatile organic compounds (VOCs), which may circumvent issues with breast density. Methods: Alveolar breath samples were collected onto Tenax TA sorbent tubes using a SohnoXB™ breath sampler. Using four desorb temperatures (75, 150, 225 and 300°C), absorption spectra were measured by infrared cavity ring-down spectroscopy (IR-CRDS), a technique for measuring absorption coefficients due to VOCs in exhaled breath. Missing values in the absorption spectra were backfilled using interpolation, and the spectrum was min-max normalized and quadratic detrended. First and second derivatives of the preprocessed absorption spectra were used as features for a support vector machine machine-learning model. Features were ranked based on minimum redundancy maximum relevance (mRMR). The top 20 ranked features were selected to limit the potential for overfitting and then optimized. Model performance was validated using non-nested leave-one-out cross-validation (LOOCV) and nested LOOCV to provide optimistic and pessimistic results, respectively. Results: Absorption spectra from 111 participants (71 positive, 40 control) were used. Of the positive subjects, 30 had low- and 31 had high-density breast tissue (measures missing for 10). Model performance is outlined. A subgroup analysis compared model performance for subjects with low- and high-density breast tissue for both non-nested and nested LOOCV models. Breast density data was not captured for control subjects thus they were not included in the subgroup analysis. Fisher’s exact test was performed to assess for significant difference between model performance for those with low- vs high-density breast tissue, resulting in a p-value of 1.00. Conclusions: Our results suggest that the classification of alveolar breath using IR-CRDS is a promising technique for the detection of breast cancer that is independent of breast density. Breath analysis may therefore become a new alternative or corroborative to mammography to support clinical decision-making. [Table: see text]
Clinicopathologic features of early stage HER2-low breast cancer.
Authors: Rebecca Nashed, Hannah Barger, Brooke Taylor Fishman, Dylan A. Schlyer, Neeharika Srivastava Makani
Journal: Journal of Clinical Oncology (2023)

e12545 Background: Breast cancer (BC) is the leading cause of cancer deaths in women worldwide. Traditionally, BC is divided into 3 categories: hormone receptor positive (HR+) if tumors overexpress either estrogen or progesterone receptors, HER2-positive (Pos) if tumors overexpress the human epidermal growth factor receptor protein (HER2), and triple negative if tumors lack overexpression of HER2, ER, or PR. 15% of all BC are HER2-Pos, which has poorer outcomes when compared to HER2-Neg. Early HER2 targeted therapies only showed benefit for treating tumors with high enough HER2 overexpression. Thus, HER2-Pos refers to tumors which stained 3+ for HER2 on immunohistochemistry (IHC) or 2+ with a positive result on amplification of the HER2 gene by fluorescence in-situ hybridization (FISH). In the recent DESTINY-Breast04 study, the drug trastuzumab deruxtecan showed benefit in treating metastatic BC patients with low levels of HER2 overexpression. HER2-Low, now a clinically relevant group, is defined as 1+ by IHC or 2+ and FISH negative. However, early stage HER2-Low BC is treated the same as HER2-Neg by the current standard of care. Large registry trials have described the HER2-Low patient population, mostly in the metastatic setting. Our study aims to describe the prevalence, pathological and clinical aspects of HER2-Low when compared to HER2-Neg BC in early stage BC patients within a community practice setting in the United States. Methods: This retrospective study analyzed 1,106 patients of which 120 were excluded due to being HER2-Pos. 986 HER2-Neg and HER2-Low patients of stages I-III were included. Patients had diagnosis dates between January 1st, 2015 and December 31st, 2022. Categorical and continuous analyses (two-proportion Z test) were performed to describe differences between HER2-Low and HER2-Neg patients at the time of diagnosis in age, tumor histology and grade, and need for chemotherapy. Results: 49% of patients (n = 1,106) were found to be HER2-Low. 91% of HER2-low patients were HR+, compared to 87% of HER2-Neg who were HR+ (p = 0.04). HER2-Low patients were more likely than HER2-Neg to have ductal carcinoma (82% vs. 75%, p = 0.01) and to be classified as grade 2 (58% vs. 48%, p = 0.001). The median age of patients with HER2-Low was 69 compared to 70 in patients with HER2-Neg disease. 36% of HER2-Low patients needed chemotherapy (neoadjuvant or adjuvant) compared to 35% who were HER2-Neg (p = 0.74). Conclusions: Our study revealed that HER2-Low patients were more likely than HER2-Neg patients to be HR+, grade 2, and to have ductal histology. In this early stage BC population, there was no difference in need for chemotherapy between HER2-Low and HER2-Neg patients. Future studies with a more racially diverse patient population looking at parameters of progression-free survival and overall survival in HER2-Low early stage BC population should be pursued.
First line combination of ribociclib and letrozole in patients (pts) with metastatic breast cancer (MBC): Focus on hepatic toxicity in the context of a real–world setting the Italian, multicenter Hermione–8 study.
Authors: Francesca Piazza, Candida Bonelli, Stefania Lui, Camilla di Nunzio, Elena Collova, Elisabetta Bozzoli, Patrizia Vici, Vittorio Gebbia, Maria Rosaria Valerio, Fable Zustovich, Paola Vanella, Luigi Coltelli, Mirco Pistelli, Francesco Giotta, Valter Torri, Marina Elena Cazzaniga
Journal: Journal of Clinical Oncology (2023)

e13064 Background: The introduction in the clinical practice of CDK4 / 6 inhibitors, in combination with endocrine therapy, has been a breakthrough in the therapeutic scenario of hormone receptor+ve/Human Epidermal growth Factor 2–ve (HR+/HER2–) MBC pts. However, despite the outstanding results in terms of OS and quality of life achieved up to now, it is important to consider that the highly selected population of clinical trials doesn’t always accurately predict the clinical impact of therapies in the general population, hence having real world data is an essential tool to guide physicians in daily clinical practice. Methods: In this observational, multicentre, prospective study, we evaluated the safety profile and the incidence of dose reductions, temporary interruptions and treatment discontinuation due to adverse events, in a real–world cohort of Italian pre or postmenopausal HR+/HER2– MBC pts who received a first line combination of ribociclib and letrozole. Results: A total of 78 MBC patients were included in the analysis. The median duration of treatment was 17 (1–61) months. At the time of ribociclib initiation, 13 (16.7%) pts already presented an altered transaminase value whereas liver metastases were present in 17 pts (21.8%). Ten (12.8%) pts experienced hepatic toxicity while on treatment. The median number of cycles for liver toxicity was 3 (1–18). The most common hepatic event was transaminase level increase in 7 (8.8%) pts. Such event occurred more frequently in the group of pts with normal baseline liver function. Hepatic toxicity was grade 1 in 3 (3.8%) pts, grade 2 in 3 (3.8%) pts, grade 3 in 3 (3.8%) pts and grade 4 in 1 (1.3%) pt. Dose reduction due to hepatic toxicity occurred in 3 (3.8%) pts, in particular one of them needed dose reduction from 600 mg to 400 mg, one from 600 mg to 200 mg whereas treatment discontinuation was applied in the last patient. Median time of treatment interruption due to hepatotoxicity was 29 (14–45) days and 3 (3.8 %) pts discontinued ribociclib due to adverse events. No deaths due to liver failure have been reported. Conclusions: Hermione–8 trial support a manageable safety profile of the combination ribociclib and letrozole in MBC patients treated in a real–world clinical setting, confirming toxicity profile in line with the results presented in the MONALEESA clinical trials. Dose reductions, temporary interruptions and discontinuation of treatment due to adverse events have been limited and seems comparable to the results from MONALEESA trials. [Table: see text]
Toxicity reporting consistency and subjective minimizing language use in colorectal cancer (CRC) and pancreatic cancer (PaC) clinical trials: A systematic review of phase III randomized controlled trials (RCTs) presented at ASCO between 2012-2022.
Authors: James Yu, Turab J Mohammed, Benjamin Chin-Yee, Clarissa Skorupski, Bishal Gyawali, Gary H. Lyman, Lauren Adkins, Lisa K. Hicks, Nicole M. Kuderer
Journal: Journal of Clinical Oncology (2023)

1567 Background: Objective and complete toxicity reporting in clinical trials is critical for patient-centered shared decision-making. Conference abstracts inform initial impressions of practice-changing treatments. Methods: We performed a systematic review of all abstracts of CRC and PaC phase 3 RCTs presented at ASCO annual meetings between 2012 – 2022; long-term follow-up, supportive care, and solely non-pharmacological studies were excluded. Objective minimization of adverse event (AE) reporting was defined as absent and/or incomplete reporting of cumulative grade 3-5 CTCAE (common terminology criteria for AE). We also assessed the use of subjective minimizing language (Chin-Yee et al ASH 2022), defined as use of “acceptable,” “tolerable”, “manageable”, “favorable” (primary minimization terms), or “feasible”, “safe”, “patients did well”, “limited” (secondary minimization terms), terms that falsely imply patients deemed the therapy as such. Presence/absence of PRO or QOL data was also assessed. Results: 63 RCTs met entry criteria (42 CRC, 21 PaC), detailed in Table. Most trials studied chemotherapy +/- other drugs (52; 83%). 17% of all abstracts did not provide any information on AE. Quantitative data on AEs were reported by 38 (60%) of abstracts. However, serious AE reporting was frequently absent (Table), with some trials reporting only specific toxicities (e.g. cytopenias) instead of cumulative CTCAE. Only 7 (11%) of abstracts noted the occurrence or absence of fatal AE. Any subjective-minimizing language was used in 15 (24%) abstracts. Notably, none of the abstracts using subjective-minimizing language provided information on fatal AE rates, nor reported on the patient perspective via QOL or PRO. Average grade ≥ 3 AE in the experimental arm were similar in abstracts with vs without minimizing language (44% vs 45%). Conclusions: Our systematic review of ph 3 RCTs in GI oncology presented at ASCO annual meetings reveals that subjective minimizing language is often used to describe serious toxicities, and without formally assessing the patient voice. Serious AE reporting is frequently absent or incomplete.[Table: see text]
De-escalating therapy dilemma in small HER2 positive node negative breast cancer.
Authors: Nawale Hajjaji
Journal: Journal of Clinical Oncology (2023)

e12626 Background: Neoadjuvant therapy (NAT) is the standard of care for locally advanced HER2 positive breast cancer (BC) and provides pathologic complete response (pCR), a key prognostic factor and indicator to decide whether to escalate to adjuvant T-DM1 in case of residual disease, as per the KRISTINE trial. However, optimal sequencing of treatment (NAT vs. surgery first) is less clear in T1cN0 (stage I) HER2 positive BC. Moreover, the long-term follow-up of the Adjuvant Paclitaxel and Trastuzumab (APT) trial showed that deescalating chemotherapy is a possible strategy for small HER2-positive node negative breast cancers when tumor size is 3 cm or less. In clinical practice, there is a recurrent debate in multidisciplinary boards to decide the adequate strategy in small HER2 positive node negative BC. Although these tumors are considered of good prognosis, recent results by An et al. 2022 fuels the debate. They showed in a large observational cohort that T1N0 HER2 positive BC APT eligible treated with NAT and not achieving pCR have similar survival to patients with T2N0 tumors with residual disease, suggesting a higher risk group among small tumors.The aim of the study was to analyze the profile and outcome of APT eligible patients treated with NAT using a detailed tumor size breakdown. Methods: APT eligible patients treated with NAT were identified among a real-world cohort of 340 early HER2 positive BC patients receiving NAT at Oscar Lambret Cancer Center (Lille, France). The outcome of the APT eligible patients (n = 115) was analyzed according to tumor size ( &lt; 15mm, 15-20mm, 21-30mm). Results: All patients were female with a median age of 54 years and received neoadjuvant anthracyclines followed by taxanes and trastuzumab. The ratio of hormone receptor (HR) positive / HR negative tumors was 72% / 28%. A similar distribution of grade 2 / grade 3 tumors was observed. Up to 75% of the patients did not have a complete pathologic response to NAT. In HR positive, the pCR rate was 43% in HER2 positive tumor of less than 15mm, 26% in tumors of 15-20mm, 25% in tumors of 21-30mm, and 32% in tumors of 31-50mm. In HR negative tumors, pCR rate was 81% in tumors of 15-20mm, 56% in tumors of 21-30mm, and 67% in tumors of 31-50mm. Conclusions: These results showed that APT eligible small HER2 positive and HR positive tumors had low chemosensitivity leading to adjuvant treatment escalation as per standard of care. It raises questions about the appropriate selection of patients for de-escalation in this population subset.
SEER analysis of 9-year breast cancer specific mortality (BCSM) in patients (pts) with invasive lobular breast cancer (ILC) assessed by the 21-gene Breast Recurrence Score assay.
Authors: Charles E. Geyer, John Bennett, Gong Tang, Jennifer M. Racz, Christy Ann Russell, Jung S. Byun, Julia Foldi, Frederick L. Baehner, Valentina I. Petkov
Journal: Journal of Clinical Oncology (2023)

554 Background: Linking of the results of the 21-gene Breast Recurrence Score (RS) commercial assay to SEER registries provides opportunity to assess real world prognostic performance of the assay in important subgroups of early breast cancer (BC). ILC is less common than invasive ductal carcinoma (IDC) and the performance of the RS assay in ILC is of interest. The relationship between RS results and 5-year BCSM in patients with ILC was reported based on a linkage in 2015 at this meeting in 2017. Here we present a comparison of 9-year BCSM of ILC vs IDC from a linkage update in 2019. These results will be updated further based on a new linkage of RS data to be completed in April 2023. Methods: Eligible pts had 0-3 axillary nodes at initial surgery, were hormone receptor positive and HER2-negative with a RS result, had no prior malignancy, and were diagnosed between January 2004 and December 2012. Pts with ICD-O-3 code 8520 were categorized as ILC and those with code 8500 as IDC. 9-year BCSM of both cohorts was estimated using actuarial methods. Multivariable Cox proportional hazards models characterized association between RS results and BCSM. Results: Of 89818 pts, 9835 (11.0%) had ILC and 64669 (72.0%) had IDC. Among pts with ILC, median age was 60 years; 12.5% were N1 and 28.4%, 63.7% and 7.9% were grade 1, 2 and 3. Median follow-up was 84 months. Chemotherapy (CT) use and BCSM increased with increasing RS result in both cohorts. After adjusting for age, race, tumor grade, tumor size, nodal status, and histologic subtype, the RS result was independently associated with BCSM ( p &lt; .001) in both ILC and IDC. Conclusions: In this linked SEER analysis of pts with ILC or IDC, the RS results were prognostic for 9-year BCSM, regardless of nodal status. [Table: see text]